Data-centric exploration using intake, dask, hvplot, and more
summary
Shows an end-to-end, reproducible workflow using intake catalogs, xarray and dask to read parquet and Landsat tiles, datashader/HVPlot to rasterize and compute NDVI and land surface temperature, and Panel plus Binder to build deployable dashboards. Uses three real datasets: daily Anaconda downloads too big for memory, Landsat scenes for LST, and ~100,000 Philly street trees. Demonstrates static JS linking to make snappy sliders and data-shader rasterize so the HTML exports work without a Python server.
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chapters (7)
- 0:00Introduction
- 3:31Ingesting data with intake
- 8:16Building dashboards with panel
- 12:26Exploring satellite imagery with HVPlot
- 22:44Overlaying tree locations on maps
- 24:30Creating interactive heat dashboard
- 30:13Q&A
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